import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
import matplotlib.pyplot as plt
data = pd.read_csv("IPL 2022 dataset.csv")
data
| match_id | date | venue | team1 | team2 | stage | toss_winner | toss_decision | first_ings_score | first_ings_wkts | second_ings_score | second_ings_wkts | match_winner | won_by | margin | player_of_the_match | top_scorer | highscore | best_bowling | best_bowling_figure | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | March 26,2022 | Wankhede Stadium, Mumbai | Chennai | Kolkata | Group | Kolkata | Field | 131 | 5 | 133 | 4 | Kolkata | Wickets | 6 | Umesh Yadav | MS Dhoni | 50 | Dwayne Bravo | 3--20 |
| 1 | 2 | March 27,2022 | Brabourne Stadium, Mumbai | Delhi | Mumbai | Group | Delhi | Field | 177 | 5 | 179 | 6 | Delhi | Wickets | 4 | Kuldeep Yadav | Ishan Kishan | 81 | Kuldeep Yadav | 3--18 |
| 2 | 3 | March 27,2022 | Dr DY Patil Sports Academy, Mumbai | Banglore | Punjab | Group | Punjab | Field | 205 | 2 | 208 | 5 | Punjab | Wickets | 5 | Odean Smith | Faf du Plessis | 88 | Mohammed Siraj | 2--59 |
| 3 | 4 | March 28,2022 | Wankhede Stadium, Mumbai | Gujarat | Lucknow | Group | Gujarat | Field | 158 | 6 | 161 | 5 | Gujarat | Wickets | 5 | Mohammed Shami | Deepak Hooda | 55 | Mohammed Shami | 3--25 |
| 4 | 5 | March 29,2022 | Maharashtra Cricket Association Stadium,Pune | Hyderabad | Rajasthan | Group | Hyderabad | Field | 210 | 6 | 149 | 7 | Rajasthan | Runs | 61 | Sanju Samson | Aiden Markram | 57 | Yuzvendra Chahal | 3--22 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 69 | 70 | May 22,2022 | Wankhede Stadium, Mumbai | Hyderabad | Punjab | Group | Hyderabad | Bat | 157 | 8 | 160 | 5 | Punjab | Wickets | 5 | Harpreet Brar | Liam Livingstone | 49 | Harpreet Brar | 3--26 |
| 70 | 71 | May 24,2022 | Eden Gardens, Kolkata | Gujarat | Rajasthan | Playoff | Gujarat | Field | 188 | 6 | 191 | 3 | Gujarat | Wickets | 7 | David Miller | Jos Buttler | 89 | Hardik Pandya | 1--14 |
| 71 | 72 | May 25,2022 | Eden Gardens, Kolkata | Banglore | Lucknow | Playoff | Lucknow | Field | 207 | 4 | 193 | 6 | Banglore | Runs | 14 | Rajat Patidar | Rajat Patidar | 112 | Josh Hazlewood | 3--43 |
| 72 | 73 | May 27,2022 | Narendra Modi Stadium, Ahmedabad | Banglore | Rajasthan | Playoff | Rajasthan | Field | 157 | 8 | 161 | 3 | Rajasthan | Wickets | 7 | Jos Buttler | Jos Buttler | 106 | Prasidh Krishna | 3--22 |
| 73 | 74 | May 29,2022 | Narendra Modi Stadium, Ahmedabad | Gujarat | Rajasthan | Final | Rajasthan | Bat | 130 | 9 | 133 | 3 | Gujarat | Wickets | 7 | Hardik Pandya | Shubman Gill | 45 | Hardik Pandya | 3--17 |
74 rows × 20 columns
data.columns
Index(['match_id', 'date', 'venue', 'team1', 'team2', 'stage', 'toss_winner',
'toss_decision', 'first_ings_score', 'first_ings_wkts',
'second_ings_score', 'second_ings_wkts', 'match_winner', 'won_by',
'margin', 'player_of_the_match', 'top_scorer', 'highscore',
'best_bowling', 'best_bowling_figure'],
dtype='object')
figure=px.bar(data,x=data['match_winner'],title='Number of matches won in IPL 2022')
figure.show()
data['won_by']=data['won_by'].map({'Wickets':'Chasing','Runs':'Defending'})
won_by=data['won_by'].value_counts()
label=won_by.index
counts=won_by.values
colors=['red','lightgreen']
fig=go.Figure(data=[go.Pie(labels=label,values=counts)])
fig.update_layout(title_text="Number of matches won by Defending v/s Chasing")
fig.update_traces(hoverinfo='label+percent',textinfo='value',textfont_size=30,marker=dict(colors=colors,line=dict(color='black',width=3)))
fig.show()
figure=px.bar(data,x=data['best_bowling'],title="Best Bowler of IPL 2022")
figure.show()
figure=px.bar(data,x=data['player_of_the_match'],title='Best Player of IPL2022')
figure.show()
figure=px.bar(data,x=data['top_scorer'],y=data['highscore'],color=data['highscore'],title = 'Top Scorer of IPl2022')
figure.show()